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---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: track_traininglogs2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# track_traininglogs2
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3388
- Precision: 0.8871
- Recall: 0.8800
- F1: 0.8835
- Accuracy: 0.9465
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6119 | 1.0 | 684 | 0.2890 | 0.8515 | 0.7911 | 0.8202 | 0.9172 |
| 0.2969 | 2.0 | 1368 | 0.2478 | 0.8720 | 0.8279 | 0.8494 | 0.9302 |
| 0.1876 | 3.0 | 2052 | 0.2418 | 0.8354 | 0.8737 | 0.8541 | 0.9332 |
| 0.1476 | 4.0 | 2736 | 0.2480 | 0.8697 | 0.8620 | 0.8658 | 0.9378 |
| 0.1302 | 5.0 | 3420 | 0.2707 | 0.8692 | 0.8697 | 0.8694 | 0.9405 |
| 0.0798 | 6.0 | 4104 | 0.2641 | 0.8755 | 0.8798 | 0.8776 | 0.9434 |
| 0.0642 | 7.0 | 4788 | 0.2694 | 0.8897 | 0.8661 | 0.8777 | 0.9449 |
| 0.0502 | 8.0 | 5472 | 0.3050 | 0.8878 | 0.8741 | 0.8809 | 0.9462 |
| 0.0267 | 9.0 | 6156 | 0.3379 | 0.8888 | 0.8750 | 0.8818 | 0.9453 |
| 0.0273 | 10.0 | 6840 | 0.3388 | 0.8871 | 0.8800 | 0.8835 | 0.9465 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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